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auto scale support

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This commit is contained in:
David Brazda
2024-10-09 16:06:19 +02:00
parent dfe1eafba9
commit 9fca26db4b
3 changed files with 165 additions and 38 deletions
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7
lightweight_charts/abstract.py
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@ -245,9 +245,12 @@ class SeriesCommon(Pane):
if format_cols:
df = self._df_datetime_format(df, exclude_lowercase=self.name)
if self.name:
if self.name not in df:
if self.name and len(df.columns) == 1: #if only one col rename it
df.columns = ['value']
elif self.name not in df:
raise NameError(f'No column named "{self.name}".')
df = df.rename(columns={self.name: 'value'})
else:
df = df.rename(columns={self.name: 'value'})
self.data = df.copy()
self._last_bar = df.iloc[-1]
self.run_script(f'{self.id}.series.setData({js_data(df)}); ')

190
lightweight_charts/helpers.py
View File

@ -1,16 +1,46 @@
from ast import parse
from .widgets import JupyterChart
from .util import (
is_vbt_indicator, get_next_color
)
import pandas as pd
#default settings for each pricescale
ohlcv_cols = ['close', 'volume', 'open', 'high', 'low']
right_cols = ['vwap']
left_cols = ['rsi', 'cci', 'macd', 'macdsignal']
middle1_cols = ["mom"]
middle2_cols = ["updated"]
histogram_cols = ['buyvolume', 'sellvolume', 'trades', 'macdhist']
def append_scales(df, right, histogram, left, middle1, middle2, name = ""):
if isinstance(df, pd.DataFrame):
for col in df.columns:
match col:
case c if c.lower() in ohlcv_cols:
continue
case c if c.lower() in right_cols:
right.append((df[c],name+c,))
case c if c.lower() in histogram_cols:
histogram.append((df[c],name+c,))
case c if c.lower() in left_cols:
left.append((df[c],name+c,))
case c if c.lower() in middle1_cols:
middle1.append((df[c],name+c,))
case c if c.lower() in middle2_cols:
middle2.append((df[c],name+c,))
case _:
right.append((df[c],name+c,))
else: #it is series (as df multiindex can be just envelope for series)
right.append((df,str(df.name),))
def append_or_extend(target_list, value):
if isinstance(value, list):
target_list.extend(value) # Extend if it's a list
else:
target_list.append(value) # Append if it's a single value
def extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs):
def extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, auto_scale, kwargs):
"""
Mutate lists based on kwargs for accessor.
Used when user added additional series to kwargs when using accessor.
@ -26,7 +56,9 @@ def extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs):
if 'middle1' in kwargs:
append_or_extend(middle1, kwargs['middle1'])
if 'middle2' in kwargs:
append_or_extend(middle1, kwargs['middle2'])
append_or_extend(middle2, kwargs['middle2'])
if 'auto_scale' in kwargs:
append_or_extend(auto_scale, kwargs['auto_scale'])
return ohlcv #as tuple is immutable
@ -67,14 +99,16 @@ class PlotSRAccessor:
middle1 = []
middle2 = []
histogram = []
auto_scale = []
#if there are additional series in kwargs add them too
#ohlcv is returned as it is tuple thus immutable
ohlcv = extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs)
ohlcv = extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, auto_scale, kwargs)
right.append((self._obj,name))
pane1 = Panel(
auto_scale=auto_scale,
ohlcv=ohlcv,
histogram=histogram,
right=right,
@ -125,39 +159,36 @@ class PlotDFAccessor:
if "size" not in kwargs:
kwargs["size"] = "xs"
#default settings for each pricescale
ohlcv_cols = ['close', 'volume', 'open', 'high', 'low']
right_cols = ['vwap']
left_cols = ['rsi']
middle1_cols = []
middle2_cols = []
histogram_cols = ['buyvolume', 'sellvolume', 'trades']
ohlcv = ()
right = []
left = []
middle1 = []
middle2 = []
histogram = []
auto_scale = []
for col in self._obj.columns:
if col in right_cols:
right.append((self._obj[col],col,))
if col in histogram_cols:
histogram.append((self._obj[col],col,))
if col in left_cols:
left.append((self._obj[col],col,))
if col in middle1_cols:
middle1_cols.append((self._obj[col],col,))
if col in middle2_cols:
middle2_cols.append((self._obj[col],col,))
if isinstance(self._obj.columns, pd.MultiIndex):
for col_tuple in self._obj.columns:
# Access the data for each column tuple dynamically
df = self._obj.loc[:, col_tuple]
name = str(col_tuple)+" "
append_scales(df, right, histogram, left, middle1, middle2, name)
first_column_df = self._obj.loc[:, self._obj.columns[0]]
ohlcv = (first_column_df[ohlcv_cols],) if isinstance(first_column_df, pd.DataFrame) and first_column_df.columns in ohlcv else () #in case of multiindex only the first ohlcv is display only one ohlcv is allowed on the pane
ohlcv = (self._obj[ohlcv_cols],)
else:
append_scales(self._obj, right, histogram, left, middle1, middle2)
#add ohlcv if all columns ohlcv_cols
#column mapping enables either both lowercase and first upper
column_mapping = {key: next((col for col in self._obj.columns if col.lower() == key), None) for key in ohlcv_cols}
mapped_columns = [column_mapping[key] for key in ohlcv_cols if column_mapping[key] is not None]
ohlcv = (self._obj[mapped_columns],) if isinstance(self._obj, pd.DataFrame) and all(col in self._obj.columns.str.lower() for col in ohlcv_cols) else ()
#if there are additional series in kwargs add them too
ohlcv = extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs)
ohlcv = extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, auto_scale, kwargs)
pane1 = Panel(
auto_scale=auto_scale,
ohlcv=ohlcv,
histogram=histogram,
right=right,
@ -196,6 +227,7 @@ class Panel:
* left : list of tuples, optional
* middle1 : list of tuples, optional
* middle2 : list of tuples, optional
* auto_scale: list of objects, optional - external objects (vbt indicators) that can be automatically parsed to given scaleID
* xloc : str or slice, optional. Vectorbt indexing. Default is None.
* precision: int, optional. The number of digits after the decimal point. Apply to all lines on this pane. Default is None.
@ -227,6 +259,7 @@ class Panel:
)
pane2 = Panel(
auto_scale=[macd_vbt_ind],
ohlcv=(t1data.data["BAC"],),
right=[],
left=[(sma, "sma_below", short_signals, short_exits)],
@ -258,7 +291,8 @@ class Panel:
ch = chart([pane1], title="Chart with EntryShort/ExitShort (yellow) and EntryLong/ExitLong markers (pink)", sync=True, session=None, size="s")
```
"""
def __init__(self, ohlcv=None, right=None, left=None, middle1=None, middle2=None, histogram=None, title=None, xloc=None, precision=None):
def __init__(self, auto_scale=[],ohlcv=None, right=None, left=None, middle1=None, middle2=None, histogram=None, title=None, xloc=None, precision=None):
self.auto_scale = auto_scale
self.ohlcv = ohlcv if ohlcv is not None else ()
self.right = right if right is not None else []
self.left = left if left is not None else []
@ -382,6 +416,78 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
active_chart.markers_set(markers=xloc_me(markers, xloc), type=type, color=color if color is not None else None)
def add_to_scale(series, right, histogram, left, middle1, middle2, column,name = None):
"""
Assigns a series to a scaleId based on its name and pre-defined col names.
Args:
-----
series (pd.Series): The series to be added to a scaleId
right (list): The right scale to add to
histogram (list): The histogram scale to add to
left (list): The left scale to add to
middle1 (list): The middle1 scale to add to
middle2 (list): The middle2 scale to add to
name (str): The name of the series
Returns:
-------
None
Notes:
-----
The function checks if the series name is in the pre-defined column names
(e.g. ohlcv_cols, right_cols, histogram_cols, etc.) and assigns the series to
the corresponding scaleId. If the name is not found in any of the pre-defined
column names, the series is added to the right scale by default.
"""
if name is None:
name = column
if column.lower() in ohlcv_cols:
return
elif column.lower() in right_cols:
right.append((series, name,))
elif column.lower() in histogram_cols:
histogram.append((series, name))
elif column.lower() in left_cols:
left.append((series, name))
elif column.lower() in middle1_cols:
middle1.append((series, name))
elif column.lower() in middle2_cols:
middle2.append((series, name))
else:
right.append((series, name,))
# automatic scale assignment
if len(pane.auto_scale) > 0:
for obj in pane.auto_scale:
if is_vbt_indicator(obj): #for vbt indicators
for output in obj.output_names:
output_series = getattr(obj, output)
output_name = obj.short_name + ':' + output
output = obj.short_name if output == "real" else output
#if output_series is multiindex - add each combination to respective scaleId
if isinstance(output_series, pd.DataFrame) and isinstance(output_series.columns, pd.MultiIndex):
for col_tuple in output_series.columns:
name=output_name + " " + str(col_tuple)
series_copy = output_series.loc[:, col_tuple].copy(deep=True)
add_to_scale(series_copy, pane.right, pane.histogram, pane.left, pane.middle1, pane.middle2, output, name)
elif isinstance(output_series, pd.DataFrame) and len(output_series.columns) > 1: #in case of multicolumns
for col in output_series.columns:
name=output_name + " " + col
series_copy = output_series.loc[:, col].copy(deep=True)
add_to_scale(series_copy, pane.right, pane.histogram, pane.left, pane.middle1, pane.middle2, output, name)
elif isinstance(output_series, pd.DataFrame) and len(output_series.columns) == 1:
name=output_name + " " + output_series.columns[0]
series_copy = output_series.squeeze()
add_to_scale(series_copy, pane.right, pane.histogram, pane.left, pane.middle1, pane.middle2, output, name)
else: #add output to respective scale
series_copy = output_series.copy(deep=True)
add_to_scale(series_copy, pane.right, pane.histogram, pane.left, pane.middle1, pane.middle2, output, output_name)
# zde jsem skoncil
#vbt ind
if pane.ohlcv != ():
series, entries, exits, markers = (pane.ohlcv + (None,) * 4)[:4]
if series is None:
@ -404,8 +510,14 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
kwargs['color'] = color
if opacity is not None:
kwargs['opacity'] = opacity
tmp = active_chart.create_histogram(**kwargs) #green transparent "rgba(53, 94, 59, 0.6)"
tmp.set(xloc_me(series, xloc))
if isinstance(series, pd.DataFrame) and isinstance(series.columns, pd.MultiIndex): #multiindex handling
for col_tuple in series.columns:
kwargs = {'name': name + str(col_tuple)}
tmp = active_chart.create_histogram(**kwargs) #green transparent "rgba(53, 94, 59, 0.6)"
tmp.set(xloc_me(series.loc[:, col_tuple], xloc))
else:
tmp = active_chart.create_histogram(**kwargs) #green transparent "rgba(53, 94, 59, 0.6)"
tmp.set(xloc_me(series, xloc))
if pane.title is not None:
active_chart.topbar.textbox("title",pane.title)
@ -413,7 +525,7 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
#iterate over keys - they are all priceScaleId except of these
for att_name, att_value_tuple in vars(pane).items():
if att_name in ["ohlcv","histogram","title","xloc","precision"]:
if att_name in ["ohlcv","histogram","title","xloc","precision", "auto_scale"]:
continue
for tup in att_value_tuple:
series, name, entries, exits, markers = (tup + (None, None, None, None, None))[:5]
@ -425,9 +537,20 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
series = series.xloc[xloc] if xloc is not None else series
for output in series.output_names:
output_series = getattr(series, output)
output = name + ':' + output if name is not None else output
tmp = active_chart.create_line(name=output, priceScaleId=att_name)#, color="blue")
tmp.set(output_series)
output = name + ':' + output if name is not None else series.short_name + ":" + output
#if output_series is multiindex - create aline for each combination
if isinstance(output_series, pd.DataFrame) and isinstance(output_series.columns, pd.MultiIndex):
for col_tuple in output_series.columns:
tmp = active_chart.create_line(name=output + " " + str(col_tuple), priceScaleId=att_name)#, color="blue")
tmp.set(output_series.loc[:, col_tuple])
else:
tmp = active_chart.create_line(name=output, priceScaleId=att_name)#, color="blue")
tmp.set(output_series)
#if multiindex then unpack them all with tuple as names
elif isinstance(series, pd.DataFrame) and isinstance(series.columns, pd.MultiIndex):
for col_tuple in series.columns:
tmp = active_chart.create_line(name=str(col_tuple) if name is None else name+" "+str(col_tuple), priceScaleId=att_name)#, color="blue")
tmp.set(xloc_me(series.loc[:, col_tuple], xloc))
else:
if name is None:
name = "no_name" if not hasattr(series, 'name') or series.name is None else str(series.name)
@ -449,13 +572,14 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
active_chart.fit()
if session is not None and session:
try:
last_used_series = output_series if is_vbt_indicator(series) else series #pokud byl posledni series vbt, pak pouzijeme jeho outputy
last_used_series = output_series.loc[:, col_tuple] if isinstance(output_series, pd.DataFrame) and isinstance(output_series.columns, pd.MultiIndex) else output_series if is_vbt_indicator(series) else series #pokud byl posledni series vbt, pak pouzijeme jeho outputy
last_used_series = last_used_series.iloc[:,0] if isinstance(last_used_series, pd.DataFrame) else last_used_series #if df then use just first column
t1 = xloc_me(last_used_series, xloc)
t1 = t1.vbt.xloc[session]
target_data = t1.obj
#we dont know the exact time of market start +- 3 seconds thus we find mark first row after 9:30
# Resample the data to daily frequency and get the first entry of each day
first_row_indexes = target_data.resample('D').apply(lambda x: x.index[0])
first_row_indexes = target_data.resample('D').apply(lambda x: x.index[0] if not x.empty else None).dropna()
# Convert the indexes to a list
session_starts = first_row_indexes.to_list()

2
setup.py
View File

@ -5,7 +5,7 @@ with open('README.md', 'r', encoding='utf-8') as f:
setup(
name='lightweight_charts',
version='2.2.2',
version='2.2.3',
packages=find_packages(),
python_requires='>=3.8',
install_requires=[